Analysis of Forecast Results

Oct 13, 2025 by talynt.org 141 views

Introduction

The level of crime is a crucial indicator in assessing the security situation of a country or region. In North Sumatra Province, this issue is a serious concern that requires strategic steps to overcome them. To understand the development patterns of crime rates from 2020 to 2023, this study uses the time series data forecasting method with the Smoothing Moving Average approach. The Smoothing Moving Average method is a statistical technique used to predict future values by smoothing fluctuations in historical data. In the context of this research, this method is used to predict the level of crime based on complete data.

Background of the Study

Crime rates have been a significant concern in North Sumatra Province, with the number of criminal cases recorded increasing from year to year. The North Sumatra Provincial Government has been working to address this issue, but the effectiveness of their policies is still uncertain. To better understand the trends and patterns of crime rates, this study aims to forecast the level of crime in North Sumatra Province from 2020 to 2023 using the Smoothing Moving Average method.

Methodology

The Smoothing Moving Average method is a statistical technique used to predict future values by smoothing fluctuations in historical data. In this study, the crime rate data from 2020 to 2022 was used to forecast the crime rate in 2023. The data was collected from the North Sumatra Provincial Police and consisted of the number of criminal cases recorded each year. The Smoothing Moving Average method was applied to the data to predict the crime rate in 2023.

Results

The forecasting results show that there is a significant increase trend in crime rates. This can be interpreted as a sign that the potential threat to security in the area is getting higher. In other words, if there are no mitigation steps taken, crime rates can continue to increase, causing negative impacts for the community and the overall quality of life. The number of criminal cases recorded was 41,298 in 2020, increased to 42,855 in 2021, then reached 44,412 in 2022, and was predicted to reach 45,969 in 2023.

Analysis of Forecast Results

The forecasting results show that the crime rate in North Sumatra Province has increased significantly from 2020 to 2023. This can be attributed to various factors, including the increasing population, poverty, and unemployment. The results of this study can be a reference for policy makers to formulate prevention strategies, such as increasing supervision, resource allocation, and community programs that can encourage reducing crime rates.

Relevance for Government Policy

With this analysis, the North Sumatra Provincial Government is expected to take more appropriate and measurable actions in dealing with security problems. Using data obtained from this forecasting method, policies can be made based on facts, not just assumptions. Through a data-based approach, it is hoped that the public will feel safer and the government will be more responsive in dealing with issues related to crime.

Implications of the Study

The results of this study have significant implications for the North Sumatra Provincial Government. The government can use the forecasting results to inform their policies and strategies for addressing crime rates. The study highlights the importance of using data-driven approaches to inform policy decisions, rather than relying on assumptions or intuition. By using the Smoothing Moving Average method, the government can make more informed decisions about how to allocate resources and prioritize their efforts.

Conclusion

The crime rate in North Sumatra Province shows a significant increase in pattern from 2020 to 2023, as predicted by the Smoothing Moving Average method. This study provides valuable information for the government in formulating policies that can overcome security problems and improve the quality of life of the community. By utilizing the right forecasting techniques, it is expected that the actions taken will be able to reduce crime rates and increase security in the community.

Recommendations

Based on the results of this study, the following recommendations are made:

The North Sumatra Provincial Government should use the forecasting results to inform their policies and strategies for addressing crime rates.
The government should prioritize the allocation of resources to address the root causes of crime, such as poverty and unemployment.
The government should implement community programs that can encourage reducing crime rates, such as education and job training programs.
The government should increase supervision and resource allocation to address the increasing crime rate.

Limitations of the Study

This study has several limitations, including:

The data used in this study was limited to the number of criminal cases recorded each year, and did not include other relevant factors, such as the type of crime or the location of the crime.
The Smoothing Moving Average method used in this study is a simple forecasting technique, and may not capture the complexity of the crime rate data.
The study did not consider the potential impact of external factors, such as economic conditions or social trends, on the crime rate.

Future Research Directions

Future research should aim to address the limitations of this study by:

Collecting more comprehensive data on crime rates, including the type of crime and the location of the crime.
Using more advanced forecasting techniques, such as machine learning or econometric models, to capture the complexity of the crime rate data.
Considering the potential impact of external factors, such as economic conditions or social trends, on the crime rate.

By addressing these limitations and future research directions, this study can provide a more comprehensive understanding of the crime rate in North Sumatra Province and inform more effective policies and strategies for addressing crime rates.

Frequently Asked Questions

This article aims to provide answers to some of the most frequently asked questions related to the forecasting of crime level in North Sumatra Province in 2020-2023 using the Smoothing Moving Average method.

Q: What is the Smoothing Moving Average method?

A: The Smoothing Moving Average method is a statistical technique used to predict future values by smoothing fluctuations in historical data. In the context of this research, this method is used to predict the level of crime based on complete data.

Q: What are the benefits of using the Smoothing Moving Average method?

A: The benefits of using the Smoothing Moving Average method include:

It is a simple and easy-to-use forecasting technique.
It can be used to predict future values based on historical data.
It can help to identify trends and patterns in the data.
It can be used to make informed decisions about resource allocation and policy implementation.

Q: What are the limitations of the Smoothing Moving Average method?

A: The limitations of the Smoothing Moving Average method include:

It is a simple forecasting technique and may not capture the complexity of the crime rate data.
It may not be suitable for forecasting data with high levels of variability or non-linearity.
It may not be able to capture the impact of external factors on the crime rate.

Q: What are the implications of the study for the North Sumatra Provincial Government?

A: The implications of the study for the North Sumatra Provincial Government include:

The government should use the forecasting results to inform their policies and strategies for addressing crime rates.
The government should prioritize the allocation of resources to address the root causes of crime, such as poverty and unemployment.
The government should implement community programs that can encourage reducing crime rates, such as education and job training programs.

Q: What are the recommendations for future research?

A: The recommendations for future research include:

Collecting more comprehensive data on crime rates, including the type of crime and the location of the crime.
Using more advanced forecasting techniques, such as machine learning or econometric models, to capture the complexity of the crime rate data.
Considering the potential impact of external factors, such as economic conditions or social trends, on the crime rate.

Q: What are the potential applications of the study?

A: The potential applications of the study include:

Informing policy decisions about resource allocation and crime prevention strategies.
Developing more effective community programs to reduce crime rates.
Improving the overall quality of life for citizens in North Sumatra Province.

Q: What are the potential limitations of the study?

A: The potential limitations of the study include:

The study is based on historical data and may not capture the impact of future events or trends.
The study may not be generalizable to other regions or countries.
The study may not capture the complexity of the crime rate data.

Q: What are the potential future directions for the study?

A: The potential future directions for the study include:

Collecting more comprehensive data on crime rates, including the type of crime and the location of the crime.
Using more advanced forecasting techniques, such as machine learning or econometric models, to capture the complexity of the crime rate data.
Considering the potential impact of external factors, such as economic conditions or social trends, on the crime rate.

By addressing these questions and providing answers, this article aims to provide a more comprehensive understanding of the forecasting of crime level in North Sumatra Province in 2020-2023 using the Smoothing Moving Average method.